Intelligence artificielle et chimie numérique : pour régler son cas à la lignine

Affiche présentée dans le cadre du Colloque de l'ARC, «Pour que la formation de la relève scientifique soit sur toutes les lèvres», dans le cadre du 87e Congrès de l'Acfas, Université du Québec en Outaouais (UQO), Gatineau, le 28 mai 2019.La lignine, un coproduit de l’industrie papetière, est le deuxième biopolymère le plus abondant sur Terre après la cellulose. Actuellement, cette lignine résiduelle est majoritairement brûlée pour produire de la chaleur. On peut donc espérer une meilleure valorisation de la lignine, mais cette amélioration passe par la connaissance de sa structure moléculaire. Comme il s’agit d’un polymère désordonné, formé d’un grand nombre d’unités fondamentales assemblées de façon combinatoire, l’intelligence artificielle (IA) aiderait à élucider le problème, et ce, à l’image de l’industrie pharmaceutique, qui a déjà recours à ces techniques pour la recherche sur de nouveaux médicaments. Pour déterminer la structure moléculaire d’une lignine à partir d’un ou de plusieurs résultats expérimentaux, il est proposé de créer numériquement une multitude de lignines potentielles et de calculer théoriquement les propriétés physiques de chacune. Cette banque de lignines alimentera ensuite un procédé d’IA qui pourra, par interpolation, produire une structure moléculaire émulant des résultats expérimentaux qu'on lui aura fournis. Déjà, de nouveaux outils ont été créés pour fabriquer des lignines numériques semblables aux lignines naturelles. L’implantation d’outils de calculs de propriétés moléculaires est en cours et le matériel permettant les calculs d’intelligence artificielle est en place. Ici comme dans bien des domaines, l'IA semble être un outil prometteur pour l’avancement des connaissances

Creation of a participatory database of bioenergy projects

Bioenergy is part of the solution to decarbonize energy systems and the economy, and to decrease greenhouse gases emissions drastically. The main goal of this work is to present a participatory database of bioenergy projects, initially based on information available on the International Energy Agency website. This new database aims at being updated over time through data crowdsourcing and being easily exportable in a spreadsheet for further processing. It provides numerous information about bioenergy projects around the world like the types of technology, inputs, outputs, financial information and project status. A detailed overview of the current database is presented, as well as the modus operandi suggested to improve over time this resource through voluntary contributions. The growing quality of this database will serve future research projects and analysis, while being a relevant tool to contribute to the success of the bioenergy sector

Pulp and paper mill sludge management practices : what are the challenges to assess the impacts on greenhouse gas emissions?

Pulp and paper mill sludge (PPMS) is an organic residual generated from the wastewater treatments. PPMS management involves economic, environmental and social costs that will likely increase in the future as landfilling tends to be reduced or banned in certain jurisdictions. The reduction or the banning of landfilling may be considered as a climate change mitigation measure since organic waste disposal is normally associated with greenhouse gas (GHG) emissions. This critical review aims to (1) describe the variety of the current and emerging PPMS management practices that are alternatives to landfilling and (2) underline the crucial need for GHG emission assessments. The management practices of the three main PPMS types (primary, secondary and de-inking) comprised in this review are land application (agriculture, silviculture, land reclamation and composting), energy recovery (combustion, anaerobic digestion, pyrolysis, bioethanol, hydrogen production and direct liquefaction) and integration in materials (biocomposite, cement, asphalt and adsorbent–absorbent). Future research should focus to increase the comprehension of known GHG determinants from the PPMS management practices and reveal unknown factors. Life cycle analyses, based on direct GHG emission measurements, are needed to determine GHG emissions from current and emerging practices and plan a responsible future reduction or banning of landfilling. Such analyses will contribute to assist decision makers in implementing the best PPMS management practices with the least impact on climate change

Smart campuses : extensive review of the last decade of research and current challenges

Novel intelligent systems to assist energy transition and improve sustainability can be deployed at different scales, ranging from a house to an entire region. University campuses are an interesting intermediate size (big enough to matter and small enough to be tractable) for research, development, test and training on the integration of smartness at all levels, which has led to the emergence of the concept of “smart campus” over the last few years. This review article proposes an extensive analysis of the scientific literature on smart campuses from the last decade (2010-2020). The 182 selected publications are distributed into seven categories of smartness: smart building, smart environment, smart mobility, smart living, smart people, smart governance and smart data. The main open questions and challenges regarding smart campuses are presented at the end of the review and deal with sustainability and energy transition, acceptability and ethics, learning models, open data policies and interoperability. The present work was carried out within the framework of the Energy Network of the Regional Leaders Summit (RLS-Energy) as part of its multilateral research efforts on smart region

Spinal Cord Injury Reveals Multilineage Differentiation of Ependymal Cells

Spinal cord injury often results in permanent functional impairment. Neural stem cells present in the adult spinal cord can be expanded in vitro and improve recovery when transplanted to the injured spinal cord, demonstrating the presence of cells that can promote regeneration but that normally fail to do so efficiently. Using genetic fate mapping, we show that close to all in vitro neural stem cell potential in the adult spinal cord resides within the population of ependymal cells lining the central canal. These cells are recruited by spinal cord injury and produce not only scar-forming glial cells, but also, to a lesser degree, oligodendrocytes. Modulating the fate of ependymal progeny after spinal cord injury may offer an alternative to cell transplantation for cell replacement therapies in spinal cord injury

Is Predominant Clonal Evolution a Common Evolutionary Adaptation to Parasitism in Pathogenic Parasitic Protozoa, Fungi, Bacteria, and Viruses?

We propose that predominant clonal evolution (PCE) in microbial pathogens be defined as restrained recombination on an evolutionary scale, with genetic exchange scarce enough to not break the prevalent pattern of clonal population structure. The main features of PCE are (1) strong linkage disequilibrium, (2) the widespread occurrence of stable genetic clusters blurred by occasional bouts of genetic exchange ('near-clades'), (3) the existence of a "clonality threshold", beyond which recombination is efficiently countered by PCE, and near-clades irreversibly diverge. We hypothesize that the PCE features are not mainly due to natural selection but also chiefly originate from in-built genetic properties of pathogens. We show that the PCE model obtains even in microbes that have been considered as 'highly recombining', such as Neisseria meningitidis, and that some clonality features are observed even in Plasmodium, which has been long described as panmictic. Lastly, we provide evidence that PCE features are also observed in viruses, taking into account their extremely fast genetic turnover. The PCE model provides a convenient population genetic framework for any kind of micropathogen. It makes it possible to describe convenient units of analysis (clones and near-clades) for all applied studies. Due to PCE features, these units of analysis are stable in space and time, and clearly delimited. The PCE model opens up the possibility of revisiting the problem of species definition in these organisms. We hypothesize that PCE constitutes a major evolutionary strategy for protozoa, fungi, bacteria, and viruses to adapt to parasitism